Jan. 31, 2024, 4:43 p.m. | Nisha Huang, Weiming Dong, Yuxin Zhang, Fan Tang, Ronghui Li, Chongyang Ma, Xiu Li, Changsheng Xu

cs.CV updates on arXiv.org arxiv.org

Large-scale text-to-image generative models have made impressive strides,
showcasing their ability to synthesize a vast array of high-quality images.
However, adapting these models for artistic image editing presents two
significant challenges. Firstly, users struggle to craft textual prompts that
meticulously detail visual elements of the input image. Secondly, prevalent
models, when effecting modifications in specific zones, frequently disrupt the
overall artistic style, complicating the attainment of cohesive and
aesthetically unified artworks. To surmount these obstacles, we build the
innovative unified …

array arts arxiv challenges creative cs.cv diffusion editing generative generative models image images multimodal prompts quality scale struggle synthesis text text-to-image textual vast visual

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